ReviewJournal of advances in medical education & professionalism2025
Integrating Artificial Intelligence in Medical Education: A Meta-Synthesis of Potentials and Pitfalls of ChatGPT.
Review in Journal of advances in medical education & professionalism, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The effectiveness of GAI-assisted teaching methods in medical education: a systematic review and meta-analysis.Frontiers in public health · 2026Pooled it
- Benchmarking Large Language Models for Scientific Writing: A Mixed‑Methods Evaluation of Chatgpt, Deepseek, and Human Authors.Journal of advances in medical education & professionalism · 2026Article
- Mapping Personalized Learning in Medical Education: A Meta-Synthesis of Artificial Intelligence Applications.Journal of advances in medical education & professionalism · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: ChatGPT serves as a double-edged sword in education, offering either constructive information or potential challenges. Its impact ranges from being a transformative tool to a disruptive force, making it difficult to evaluate its educational efficacy comprehensively. In light of this complexity, the primary aim of this research was to investigate the opportunities and challenges associated with the integration of ChatGPT into the domain of medical education. Methods: The study utilized the Interaction Equivalency Theorem as its conceptual framework to guide the investigation. To achieve the research objectives, a meta-synthesis of the literature was conducted to systematically integrate the findings of selected studies. Data collection involved comprehensive searches across specialized academic databases, including Science Direct, Springer, ERIC, Emerald, SAGE, Wiley Online Library, PubMed, and Google Scholar, focusing on publications from 2022 to 2024. 88 articles were meticulously selected based on their relevance to the research topic. The data were then subjected to thematic analysis, facilitating the extraction of key insights and patterns to address the study objectives. Results: The findings were organized into four primary subthemes highlighting the opportunities presented by ChatGPT in medical education. These sub-themes encompassed benefits for educators, learners, curriculum development, and the learning process. Similarly, the challenges related to the integration of ChatGPT were categorized into four primary sub-themes: addressing the difficulties experienced by educators, learners, curriculum development, and the learning process. Together, these challenges were further delineated into 11 secondary sub-themes, offering a comprehensive analysis of the complexities involved. Conclusion: The findings suggest that improving educational efficiency, assisting with self-development, enhancing communication skills, creating and expanding curriculum, and improving the learning environment are opportunities for utilizing ChatGPT. The study outcomes also reveal that lack of technological knowledge, negative attitudes, reduction in education quality, diminishing students' capabilities, reducing learning quality, flaws in learning development, difficulties in designing educational content, and bias in learning evaluation are challenges of applying ChatGPT in medical education.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.